논문 해외 국제전문학술지(SCI급) A scenario-based stochastic programming approach for the public charging station location problem
- 학술지 구분 국제전문학술지(SCI급)
- 게재년월 2022-02
- 저자명 Seheon Kim, Soora Rasouli, Harry JP Timmermans, Dujuan Yang
- 학술지명 Transportmetrica B: Transport Dynamics
- 발행처명 TAYLOR & FRANCIS LTD
- 발행국가 해외
- 논문언어 외국어
- 전체저자수 4
- 연구분야 공학 > 교통공학
- 원문 링크 https://doi.org/10.1080/21680566.2021.1997672
홈페이지논문 초록 (Abstract)
This paper presents an integrated framework for the optimal planning of public charging stations for plug-in electric vehicles (PEVs) in urban areas. The framework consists of two main components: (i) an out-of-home charging demand model based on an activity-based travel demand model, and (ii) a public charging station location-allocation model using a scenario-based stochastic programming (SP) approach. In order to capture the dynamic charging behaviour of PEV users, a chi-squared automatic interaction detector (CHAID)-based mixed effects decision tree is induced from multi-day activity diaries. Moreover, because the stochastic error of the micro-simulation approach brings about uncertainty, we adopted a two-stage stochastic mixed-integer programming (TSMIP) model, which measures uncertainty by means of a finite set of scenarios obtained from the derived decision rules underlying PEV charging. The proposed approach is demonstrated for the City of Eindhoven, The Netherlands, and benefits of the stochastic solution are discussed.